IntroductionAlzheimer's disease (AD) is a progressive neurodegenerative disease resulting in memory loss and cognitive decline. Synaptic dysfunction is an early hallmark of the disease whose effects on whole-brain functional architecture can be identified using resting-state functional MRI (rsfMRI). Insights into mechanisms of early, whole-brain network alterations can help our understanding of the functional impact of AD's pathophysiology.MethodsHere, we obtained rsfMRI data in the TgF344-AD rat model at the pre- and early-plaque stages. This model recapitulates the major pathological and behavioral hallmarks of AD. We used co-activation pattern (CAP) analysis to investigate if and how the dynamic organization of intrinsic brain functional networks states, undetectable by earlier methods, is altered at these early stages.ResultsWe identified and characterized six intrinsic brain states as CAPs, their spatial and temporal features, and the transitions between the different states. At the pre-plaque stage, the TgF344-AD rats showed reduced co-activation of hub regions in the CAPs corresponding to the default mode-like and lateral cortical network. Default mode-like network activity segregated into two distinct brain states, with one state characterized by high co-activation of the basal forebrain. This basal forebrain co-activation was reduced in TgF344-AD animals mainly at the pre-plaque stage. Brain state transition probabilities were altered at the pre-plaque stage between states involving the default mode-like network, lateral cortical network, and basal forebrain regions. Additionally, while the directionality preference in the network-state transitions observed in the wild-type animals at the pre-plaque stage had diminished at the early-plaque stage, TgF344-AD animals continued to show directionality preference at both stages.DiscussionOur study enhances the understanding of intrinsic brain state dynamics and how they are impacted at the early stages of AD, providing a nuanced characterization of the early, functional impact of the disease's neurodegenerative process.

中文翻译：

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阿尔茨海默病 TgF344-AD 大鼠模型中静息脑网络状态转换的早期方向性改变

简介阿尔茨海默病（AD）是一种进行性神经退行性疾病，导致记忆丧失和认知能力下降。突触功能障碍是该疾病的早期标志，可以使用静息态功能 MRI (rsfMRI) 来识别其对全脑功能结构的影响。深入了解早期全脑网络改变的机制可以帮助我们了解 AD 病理生理学的功能影响。方法在这里，我们在 TgF344-AD 大鼠模型中获得斑块前期和早期阶段的 rsfMRI 数据。该模型概括了 AD 的主要病理和行为特征。我们使用共激活模式 (CAP) 分析来研究早期方法无法检测到的内在大脑功能网络状态的动态组织是否以及如何在这些早期阶段发生改变。结果我们识别并表征了六种内在大脑状态作为 CAP，它们的空间和时间特征，以及不同状态之间的转换。在斑块前阶段，TgF344-AD 大鼠表现出与默认模式样和外侧皮质网络相对应的 CAP 中枢区域的共激活减少。类似默认模式的网络活动分为两种不同的大脑状态，其中一种状态的特征是基底前脑的高度共同激活。 TgF344-AD 动物的这种基础前脑共激活主要在斑块前阶段减少。大脑状态转换概率在斑块前阶段在涉及默认模式样网络、外侧皮质网络和基底前脑区域的状态之间发生改变。此外，虽然在斑块前阶段在野生型动物中观察到的网络状态转换的方向性偏好在斑块早期阶段已经减弱，但 TgF344-AD 动物在两个阶段都继续表现出方向性偏好。了解大脑内在状态动态以及它们在 AD 早期阶段如何受到影响，提供对该疾病神经退行性过程的早期功能影响的细致入微的描述。